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M. Sokac, Z. Santosi, D. Vukelic, M. Katic, M.N. Durakbasa, I. Budak:
"Enhancement of Images from Industrial X-Ray Computed Tomography Systems by Hybrid Approach";
in: "Proceedings of the International Symposium for Production Research 2019, Lecture Notes in Mechanical Engineering book series (LNME)", 1; M.N. Durakbasa, G. Gencyilmaz (ed.); Springer Nature Switzerland AG, Cham, Switzerland, 2019, ISBN: 978-3-030-31343-2, 138 - 146.

Application of the computed tomography (CT) within industry has been rising in recent years due to its non-destructive abilities and accuracy. Nevertheless, there are some challenges related to CT scanning, such as pres- ence of artefacts. The aim of this research is to investigate to what extent the application of some advanced algorithms can influence the accuracy of the X-ray CT images. In this paper, after a brief overview of different existing methods used for reduction of different types of artefacts, preliminary research of a new approach for CT image enhancement is presented. It is based on a hybrid methodology using two different methods - Fuzzy Clustering and Region Growing - joined in order to exploit their advantages. Results show that the proposed methodology contributes to CT image enhancement, with borders of segmented objects on CT images more easily extracted.

Computed tomography, X-ray CT, Artefacts, Industrial CT Images, Image processing

http://dx.doi.org/10.1007/978-3-030-31343-2_45